Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T13404B922B354C93D1D870AECE3E0AA18264DE346BF2215D9A66861FF63C4DEC91577CC |
|
CONTENT
ssdeep
|
1536:e4wVwNTeECm8ArA9AsA5Dx+xF1DjvjQc6FjWYRtj4fiwCdWcgf6t34f2YCdWcsfs:e4w2mjvUtj4fiwIWcgf6t34f2YIWcsfs |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c384bcb4c3c6ccbc |
|
VISUAL
aHash
|
ff00207c6c00c0e0 |
|
VISUAL
dHash
|
c416e9c9c8080789 |
|
VISUAL
wHash
|
ff00007c7ee0e0fd |
|
VISUAL
colorHash
|
38000038000 |
|
VISUAL
cropResistant
|
008934344a898c14,c416e9c9c8080789 |
Victim enters username and password into fake login form. Credentials are captured via JavaScript and exfiltrated to attacker's server in real-time.
Malicious code is obfuscated using 53 techniques to evade detection by security scanners and make reverse engineering more difficult.
Drainer supports multiple blockchain networks and checks for high-value tokens on each chain before executing drain operations.